The present invention is related to the field of digital communications, and more particularly to techniques for equalizing channel effects in digital communication systems.
Digital communications suffers from a particular form of distortion known as intersymbol interference (ISI). ISI has been recognized as the major obstacle to high speed data transmission over mobile radio channels. Digital communications systems use an operation known as "equalization" to minimize ISI. This minimization is often achieved by minimizing a cost function which is a suitably chosen function of the data.
There are generally two approaches to equalization: conventional equalization and "blind" equalization. In systems employing conventional equalization, a training sequence is transmitted over the channel prior to the transmission of any useful data. The training sequence is a data sequence that is a priori known to the receiver. The receiver uses the relationship between the known training sequence and the sequence it actually receives to construct an approximation of the inverse transfer function for the channel. The equalizer is then configured to use the inverse transfer function and thereby induce minimal ISI.
Conventional equalization is problematic in some communication systems, such as mobile and multi-point communications systems, because the training sequences use up scarce bandwidth resources that could otherwise be used to transmit useful data. Such systems therefore often use blind equalization, which is a form of equalization that does not require the use of a training sequence.
There have been several approaches to the problem of blind equalization including a popular technique known as the Godard algorithm. These algorithms generally employ cost functions that measure the expected value of a function of the equalizer output. For example, the Godard algorithm uses a functional called the dispersion of order p (where p is a positive integer) as the cost function.
It is desirable to improve the ability of digital communications systems to minimize ISI, including communications systems employing blind equalization. Systems achieving such reduced ISI are capable of achieving reduced data error rates at prevailing data transmission rates, or can obtain higher data transmission rates without sacrificing data integrity, in order to obtain better overall system performance.